1) From the Digital Bank to the Intelligent Bank 2) How to become an AI bank
Welcome to my newsletter! Each week two hand-picked topics from the world of fintech, payments and banking with behind-the-scenes analysis!
1) From the Digital Bank to the Intelligent Bank
The digital bank is an outdated concept. Fast being replaced by the intelligent bank. The only question is how soon banks can manage the transition. Let’s take a look.
I have broken down the main elements that make up the transition to the intelligent bank:
1. From transactional to predictive banking: digital banking enabled 24/7 self-service, but intelligent banking takes it further by predicting customer needs. AI-driven models analyse real-time data to offer personalized financial insights, proactive credit offerings, and automated investment recommendations.
2. AI-powered risk & fraud management: traditional risk assessment relied heavily on historical data. Intelligent banks use AI and machine learning to detect fraud in real time, identify suspicious patterns and prevent threats before they occur.
3. Hyper-personalization: instead of generic offers, intelligent banks use AI to tailor financial products to individual customers (mass personalization).
4. Seamless omnichannel experience: customers no longer interact with banks through a single channel. Intelligent banking ensures that a user can start a transaction on a mobile app, continue it via a chatbot, and complete it with a human advisor. All while maintaining a seamless, connected experience.
5. Autonomous banking operations: intelligent banks optimize back-office processes using cloud and AI automation, reducing human errors and significantly improving efficiency. Functions such as loan approvals, compliance checks, and reconciliation are increasingly self-regulated by AI-driven workflows.
Banks are in a time race. They not only need to move from digital to intelligent but also do it fast.
In doing so technology is the biggest dependency. One of the most interesting approaches I have seen on how to best support banks in this transition is Huawei's 4-Zero model, which is based on 4 main pillars:
1. Zero Downtime → Instant Readiness
AI-powered predictive maintenance and cloud resilience ensure 24/7 availability, allowing banks to deploy and scale AI solutions without service disruptions.
2. Zero Wait → Faster Customer Experiences
AI-driven real-time processing eliminates delays in transactions, approvals, and customer interactions, making banking services ultra-responsive.
3. Zero Touch → Reduced Operational Burden
End-to-end automation using AI and machine learning removes manual intervention in processes like KYC, loan approvals, and compliance, freeing up resources for AI innovation.
4. Zero Trust → Seamless AI Integration
AI-driven security frameworks continuously validate access, ensuring trust and compliance while enabling banks to integrate AI-powered services without increasing risk.
The era of intelligent banking isn’t a distant future - it’s happening now. Banks will not be able to transform in months but getting a head start can make a difference.
Opinions and graphics: Panagiotis Kriaris
2) How to become an AI bank
AI is poised to transform banking like no other technology has done in the past. But whereas almost every bank acknowledges the need to become AI-first, there is lots of uncertainty on how to do so.
The reason why AI is so transformative doesn’t have to do with the technology per se but with the real impact that it can bring about. There is broad consensus that financial institutions can leverage AI to drive results across three main categories:
1. Hyper-personalization
2. Decision-making automation
3. Efficiency enhancement
However, the real challenge is to break down the impact in components and understand how each one can drive change. Here is a high-level overview:
1. AI-powered decision-making: AI-first banks leverage machine learning models for credit scoring, fraud detection, risk assessment, and portfolio management. Traditional banks rely on historical data, but AI banks dynamically analyze real-time data for smarter, faster decisions.
2. Hyper-personalization: AI-first banks use advanced analytics to customize financial products based on individual behaviour. From tailored investment advice to automated savings plans, AI enables a highly personalized customer experience.
3. End-to-End automation: Robotic Process Automation (RPA) and AI streamline operations, reducing costs and errors. AI-driven chatbots and virtual assistants handle customer queries, while back-office automation accelerates compliance and transaction processing.
4. AI-driven security and compliance: AI banks enhance security with biometric authentication, anomaly detection, and AI-driven compliance monitoring. Given the rise in cyber threats, AI plays a crucial role in identifying fraudulent transactions before they occur.
5. Cloud and edge computing: AI-first banks operate on scalable cloud infrastructures to process massive amounts of data in real time. Edge AI enables localized data processing for faster responses in financial transactions.
The next step has to do with putting all these elements into a coherent, top-down transformation plan. The challenge is not the plan itself but also the fact that it must happen at a fraction of the time of usual digital transformation projects. To be able to do so banks will need support. But again, here they need to do away with the old practice of providers that usually bring low added value. Instead, they need to focus on strategic partners that act not only as technology providers, but also - and majorly – as trusted consultants with high added value.
Huawei’s AI-Driven banking solutions are a good example of such a partner that can bring added value across several areas:
- RaaS for financial institutions: Huawei’s Resilience-as-a-Service (RaaS) framework provides AI-powered disaster recovery, risk management, and operational continuity. Banks leveraging RaaS ensure uninterrupted services, even in the face of cyber threats and system failures.
- Cloud + AI Integration: Huawei’s AI-powered cloud solutions offer banks high-performance computing, predictive analytics, and real-time risk assessment. This enables AI banks to scale operations efficiently.
- AI-powered fraud detection: Huawei’s AI-driven security and compliance solutions help detect fraud patterns, ensuring robust AML (Anti-Money Laundering) and KYC (Know Your Customer) processes.
- Smart branch transformation: Huawei supports the transition from traditional banking to smart, AI-powered branches with AI-assisted customer service, and intelligent financial advisory systems.
- 5G-powered AI banking: with proven leadership in 5G, Huawei enables real-time financial transactions, edge AI processing, and ultra-low-latency services, enhancing customer experience and security.
Becoming an AI bank is not just about adopting new technology - it’s about transforming the whole organization (business model, operations, security, customer engagement). But the way technology will be introduced will majorly affect the success (or not) of the entire initiative.
Opinions: Panagiotis Kriaris